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3D object retrieval using 2D line drawing and graph based relevance reedback
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Source International Multimedia Conference archive
Proceedings of the 14th annual ACM international conference on Multimedia table of contents
Santa Barbara, CA, USA
POSTER SESSION: Short papers session 1 table of contents
Pages: 105 - 108  
Year of Publication: 2006
ISBN:1-59593-447-2
Authors
Liangliang Cao  Chinese University of Hong Kong
Jianzhuang Liu  Chinese University of Hong Kong
Xiaoou Tang  Microsoft Research Asia, Beijing, China
Sponsors
ACM: Association for Computing Machinery
SIGMULTIMEDIA: ACM Special Interest Group on Multimedia
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper aims to provide a user-friendly interface for 3D object retrieval. In previous 3D retrieval systems, the user mainly uses two methods to input a query: providing an existing 3D objects, or providing partial shape information of desired objects such as text and 2D shapes. The first method fails when the user does not have a similar 3D object in hand, and the second method cannot sufficiently describe 3D shapes of objects. We believe that the best way is to have a good interface that can convert a 2D sketch drawn by the user into a 3D object as the query. A 2D line drawing is easy to be drawn and is the simplest and most direct way of illustrating a 3D object. In this paper, we develop an interface of 3D object reconstruction from line drawings, which allows the user to draw line drawings of objects with both planar and curved surfaces. In addition, in order to refine the retrieved results, we develop a relevance feedback algorithm based on a novel graph discriminant analysis. Compared with recently published relevance feedback algorithms, our algorithm achieves better retrieval performance.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Liangliang Cao: colleagues
Jianzhuang Liu: colleagues
Xiaoou Tang: colleagues